Visual AI in Healthcare: Exploring Instance Imbalance in Medical Semantic Segmentation

Current benchmarks in Medical Semantic Segmentation either leave out imbalanced datasets or focus on class imbalance. However, the nature of semantic segmentation shows that it is construed towards the segmentation of objects without differentiating multiple instances within a single class. This leads to the problem of instance imbalance in semantic segmentation. This is quite concerning in the case of medical image segmentation where the size of instances is principal. This talk will focus on a new evaluation metric and analysis of losses particularly to understand instance imbalance in semantic segmentation. About the Speaker Soumya Snigdha Kundu is a Ph.D. student at King’s College London. His work is focused on Trustworthy Machine Learning (TML) and its application to Neuro-Oncology. Recorded on Sept 19, 2024 at the Visual AI in Healthcare virtual event. #computervision #machinelearning #datascience #ai #artificialintelligence